code: def __init__(
      self,
      instruments="csi500",
      start_time=None,
      end_time=None,
      freq="day",
      infer_processors=[],
      learn_processors=_DEFAULT_LEARN_PROCESSORS,
      fit_start_time=None,
      fit_end_time=None,
      process_type=DataHandlerLP.PTYPE_A,
      filter_pipe=None,
      inst_processors=None,
      **kwargs,
  ):
      infer_processors = check_transform_proc(
          infer_processors, fit_start_time, fit_end_time
      )
      learn_processors = check_transform_proc(
          learn_processors, fit_start_time, fit_end_time
      )
      data_loader = Avg15minLoader(
          config=self.loader_config(),
          filter_pipe=filter_pipe,
          freq=freq,
          inst_processors=inst_processors,
      )
      super().__init__(
          instruments=instruments,
          start_time=start_time,
          end_time=end_time,
          data_loader=data_loader,
          infer_processors=infer_processors,
          learn_processors=learn_processors,
          process_type=process_type,
      )
  
file_path: qlib/examples/benchmarks/LightGBM/multi_freq_handler.py
imports: import pandas
  from qlib.data.dataset.loader import QlibDataLoader
  from qlib.contrib.data.handler import DataHandlerLP, _DEFAULT_LEARN_PROCESSORS, check_transform_proc
label_desc: Use image node_id 1 to create a new Avg15minHandler object from inherited base classes: DataHandlerLP with example: obj = Avg15minHandler(instruments, start_time, end_time, freq, infer_processors, learn_processors, fit_start_time, fit_end_time, process_type, filter_pipe, inst_processors)